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Critical evaluation of the Illumina MethylationEPIC BeadChip microarray for whole-genome DNA methylation profiling [MethylationEPIC]

ABSTRACT: We performed a critical evaluation of the new Infinium MethylationEPIC BeadChip microarray. EPIC covers over 850,000 CpG sites, including >90% of the CpGs from the HumanMethylation450 (HM450) BeadChip and an additional 413,743 CpGs. Even though the additional probes improve the coverage of regulatory elements, including 58% of FANTOM5 enhancers, only 7% distal and 27% proximal ENCODE regulatory elements are represented. Detailed comparisons of regulatory elements from EPIC and whole-genome bisulphite sequencing data (WGBS) show that a single EPIC probe is not always informative for those distal regulatory elements showing variable methylation across the region. However, overall data from the EPIC array at single loci are highly reproducible across technical and biological replicates and demonstrate high correlation with HM450 and WGBS data. We show that the HM450 and EPIC arrays distinguish differentially methylated probes, but the absolute agreement depends on the threshold set for each platform.

ORGANISM(S): Homo sapiens

PROVIDER: GSE86831 | GEO | 2016/09/12

SECONDARY ACCESSION(S): PRJNA342658

REPOSITORIES: GEO

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Project description:DNA methylation is a defining feature of mammalian cellular identity and is essential for normal development. Most cell types, except germ cells and pre-implantation embryos, display relatively stable DNA methylation patterns, with 70-80% of all CpGs being methylated. Despite recent advances we still have a too limited understanding of when, where and how many CpGs participate in genomic regulation. Here we report the in depth analysis of 42 whole genome bisulfite sequencing (WGBS) data sets across 30 diverse human cell and tissue types. We observe dynamic regulation for only 21.8% of autosomal CpGs within a normal developmental context, a majority of which are distal to transcription start sites. These dynamic CpGs co-localize with gene regulatory elements, particularly enhancers and transcription factor binding sites (TFBS), which allow identification of key lineage specific regulators. In addition, differentially methylated regions (DMRs) often harbor SNPs associated with cell type related diseases as determined by GWAS. The results also highlight the general inefficiency of WGBS as 70-80% of the sequencing reads across these data sets provided little or no relevant information regarding CpG methylation. To further demonstrate the utility of our DMR set, we use it to classify unknown samples and identify representative signature regions that recapitulate major DNA methylation dynamics. In summary, although in theory every CpG can change its methylation state, our results confirm that only a fraction does so as part of coordinated regulatory programs. Therefore our selected DMRs can serve as a starting point to help guide novel, more effective reduced representation approaches to capture the most informative fraction of CpGs as well as further pinpoint putative regulatory elements. Analysis of 42 human WGBS libraries comprising 30 distinct primary cell lines, tissues, in vitro derived cell types and cell lines. BiSeq raw sequencing reads were aligned using maq in bisulfite mode (Li et al. 2008) or bsmap 2.7 (Xi et al. 2009) against human genome version hg19/GRCh37, discarding duplicate reads. DNA methylation calling was performed based on an extended custom software pipeline published previously for RRBS (Gu et al., 2010). The bed files contain all seen CpGs within the given library. The number of methylated reads/number of total reads is listed in the score column. This study includes a re-analysis of Samples from the NIH Roadmap Epigenomics Mapping Consortium (REMC; GSE16256, GSE17312), Hodges et al. 2011 (GSE31971), Molaro et al. 2011 (GSE30340), and Xi et al. 2013. WARNING: This submission is incomplete pending further deposits of raw data files from Meissner via EDACC.

Dataset Information

Critical evaluation of the Illumina MethylationEPIC BeadChip microarray for whole-genome DNA methylation profiling [MethylationEPIC]

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